1. At-Home with Technology & Data

Understanding People’s Experience for Physical Activity Planning and Exploring the Impact of Historical Records on Plan Creation and Execution
説明

Making and executing physical activity plans can help people improve their physical activity levels. However, little is known about how people make physical activity plans in everyday settings and how people can be assisted in creating more successful plans. In this paper, we developed and deployed a mobile app as a probe to investigate the in-the-wild physical activity planning experience for 28 days with 17 participants. Additionally, we explored the impact of presenting successful and unsuccessful planning records on participants' planning behaviors. Based on interviews before, during, and after the deployment, we offer a description of what factors participants considered to fit their exercise plans into their existing routines, as well as factors leading to plan failures and dissatisfaction with planned physical activity. With access to historical records, participants derived insights to improve their plans, including trends in successes and failures. Based on those findings, we discuss the implications for better supporting people to make and execute physical activity plans, including suggestions for incorporating historical records into planning tools.

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The TAC Toolkit: Supporting Design for User Acceptance of Health Technologies from a Macro-Temporal Perspective
説明

User acceptance is key for the successful uptake and use of health technologies, but also impacted by numerous factors not always easily accessible nor operationalised by designers in practice. This work seeks to facilitate the application of acceptance theory in design practice through the Technology Acceptance (TAC) toolkit: a novel theory-based design tool and method comprising 16 cards, 3 personas, 3 scenarios, a virtual think-space, and a website, which we evaluated through workshops conducted with 21 designers of health technologies. Findings showed that the toolkit revised and extended designers' knowledge of technology acceptance, fostered their appreciation, empathy and ethical values while designing for acceptance, and contributed towards shaping their future design practice. We discuss implications for considering user acceptance a dynamic, multi-stage process in design practice, and better supporting designers in imagining distant acceptance challenges. Finally, we examine the generative value of the TAC toolkit and its possible future evolution.

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More than Bedtime and the Bedroom: Sleep Management as a Collaborative Work for the Family
説明

Sleep is a vital health issue. Continued sleep deficiency can increase the chance of stroke, cardiovascular disease, obesity, and diabetes. Previous studies have investigated sleep as an individual activity performed within bedrooms at night. In this study with twenty parents of young children, we identify sleep as a complex experience entangled with social dynamics between family members. For example, children's sleep means not just time for children to rest, but time for self-care for parents. This paper's contributions are twofold. First, we show how the boundaries that define sleep in terms of time (at night), space (in bedrooms), and unit of analysis (individual-focused) limit designers' opportunities to tackle the deeper sleep issues of families. Second, we suggest "division of labor" as an important but rarely discussed design concept to enhance family sleep, and as a design theme for home technologies that address issues emerging from social dynamics between householders.

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At-home Pupillometry using Smartphone Facial Identification Cameras
説明

With recent developments in medical and psychiatric research surrounding pupillary response, cheap and accessible pupillometers could enable medical benefits from early neurological disease detection to measurements of cognitive load. In this paper, we introduce a novel smartphone-based pupillometer to allow for future development in clinical research surrounding at-home pupil measurements. Our solution utilizes a NIR front-facing camera for facial recognition paired with the RGB selfie camera to perform tracking of absolute pupil dilation with sub-millimeter accuracy. In comparison to a gold standard pupillometer during a pupillary light reflex test, the smartphone-based system achieves a median MAE of 0.27mm for absolute pupil dilation tracking and a median error of 3.52\% for pupil dilation change tracking. Additionally, we remotely deployed the system to older adults as part of a usability study that demonstrates promise for future smartphone deployments to remotely collect data in older, inexperienced adult users operating the system themselves.

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